1. Field of the Invention
The present invention relates to a camera tracing and surveillance system and method for security, and more particularly, to a camera tracing and surveillance system and method for security, whereby an image having high resolution for identification in which a person can be accurately identified within a surveillance area and identity of the person can be accurately checked, can be obtained.
2. Description of the Related Art
A wide variety of types of surveillance systems using cameras have been recently used in the field of industry, and such camera surveillance systems have been actively utilized for security and crackdown.
Although some cameras for car crackdown are installed on the road in order to capture an image of a necessary area by controlling the position of a camera (adjusting an image-capturing direction), most security surveillance cameras that surveil a visitor or an invader by capturing an image of a current particular place are whole area surveillance cameras that capture an image of the whole of a surveillance area at a particular distance and within the range of a viewing angle.
Since such whole area surveillance cameras as fixed cameras surveil a predetermined wide area, they have a limitation in resolution. Thus, in most cases, a face of a person within a surveillance area cannot be accurately identified using only an image captured by a whole area surveillance camera.
Thus, a system for dynamically tracing a person using a camera has been recently developed. However, the level of tracing technology is still low and thus it is not easy to apply the tracing technology in an actual site. It is not possible to effectively trace only a person using tracing algorithms that depend on a charge-coupled device (CCD) image according to the related art, because there are a wide variety of objects that move on a screen.
As a result, technology for accurately tracing only a person and capturing an image of the person is necessary. In addition, when there are several surveillance objects, the development of technology for surveiling multiple targets is a serious problem.
Representative tracing methods according to the related art and their technical problems are as follows.
1) Representative method relating to background and object distribution (difference picture algorithm/background model)
Difference Picture Algorithm
This is a method of separating an object from a background by comparing two images delayed for a predetermined amount of time, whereby an object that moves in a fixed background can be effectively detected.
FIG. 1 illustrates an object distributed image obtained using a difference picture algorithm according to the related art.
Background Model
This is a method of adding an image of a current frame to a background image as a base by checking every previous frame of a current image, and the method is mainly used in generating a background image.                Temporal mean: it uses a mean value of pixel values of previous frames        Temporal median: it uses a value shown in a previous frame at an arbitrary pixel        
Technical Problems
When there is a minute motion or no motion, object detection is not possible (recognized as a background), and when a boundary between objects is similar to a background, false recognition occurs, and when a camera and a background move simultaneously or when only the background moves, background and object distribution is not possible.
2) Detection and tracing of moving object (feature-based method/area-based method)
Feature-Based Method                Method Using Optical Flow: it uses a feature that there is only a spatial change in two continuous frames obtained within a short time and light energy of a pixel itself is preserved.        Method Using Straight Line: it has a feature that the number of straight lines in one image is small and the straight lines themselves are clear, and thus a number of occasions of potential matching can be reduced.        Method Using Corner Point: it traces an object by featuring the shape of a moving object based on feature flow-based information.        Area-based Method: it traces an object using correlation between an image and the next image using a piece of the image in a predetermined area including a feature point of the image.        Block Matching Method: correlation is obtained using differences between mean squares and the sum of differences between absolute values of a pixel        
FIG. 2 illustrates a tracing method using extraction of feature points of an object according to the related art.
Technical Problems
An arithmetic operation for feature or block matching is complicated (delay in real-time processing), and a database relating to features of an object is required to be made on a system in order to detect the object.
3) Stereo-based object tracing (Optical JTC tracing/BPEJTC tracing)
This is technology for tracing an object by obtaining information regarding a distance between a left/right stereo input image and an object to be traced and by controlling both cameras using coordinates.                Optical Joint Transform Correlator (JTC) Tracing System: it traces a movement trajectory of an image based on measurement of a change in positions of frames by locating two target image signals on an optical JTC input plane.        Binary Phase Extraction JTC (BPEJTC) Tracing System: it uses an optical JTC having the shape of a binary phase having excellent discrimination on similar images.        
FIG. 3 illustrates a tracing method using stereo according to the related art.
Technical Problems
When there are much background noise, or backgrounds of left and right images are different from each other, or a change in background occurs due to movement of a camera, tracing is not possible.
As mentioned above, problems of tracing methods according to the related art are summarized; first, in tracing methods according to the related art, tracing is performed by detecting movement, and second, movement is traced using a difference between frames.
Consequently, it is not easy to perform these conventional methods in real-time due to the use of mathematic approach or complicated algorithms, and when there is no movement, person recognition and tracing is not possible.
FIG. 4 illustrates an example of a tracing calculation equation according to the related art, wherein L indicates a Gaussian blurring image, and G indicates a Gaussian function, and D indicates a Difference of Gaussian (DoG) function, and m indicates the size of a feature point, and θ indicates a directional vector.
Thus, the development of technology for accurately identifying an object in real-time using a simple tracing calculation equation is needed.